Vehicle and control method thereof

ABSTRACT

A vehicle includes: an input unit configured to receive an execution command for speech recognition; a calculator configured to calculate a time in which the vehicle is expected to arrive at an obstacle existing on a road on which the vehicle travels; and a speech recognition controller configured to compare the calculated time in which the vehicle is expected to arrive at the obstacle to a time in which a voice command input is expected to be completed to determine whether to perform dynamic noise removal pre-processing.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit of priority to Korean PatentApplication No. 10-2015-0103518, filed on Jul. 22, 2015 in the KoreanIntellectual Property Office, the disclosure of which is incorporatedherein by reference.

TECHNICAL FIELD

Embodiments of the present disclosure relate to a vehicle including aspeech recognition module, and a control method thereof.

BACKGROUND

Many vehicles include an Audio Video Navigation (AVN) terminal.Generally, the AVN terminal displays a control screen for controllingvarious devices installed in the vehicle or a screen for executingadditional functions that can be executed on the AVN terminal, inaddition to providing information about a route to a destination. A usercan manipulate the AVN terminal through a display with a touch screen ora jog shuttle type controller, or using a voice command to controlvarious devices in the vehicle. In the case in which the usermanipulates the AVN terminal using a voice command, the vehicle shouldbe able to recognize voice commands during traveling. Accordingly,research for improving a recognition rate of voice commands when avehicle travels has been conducted.

SUMMARY

Additional aspects of the disclosure will be set forth in part in thedescription which follows and, in part, will be obvious from thedescription, or may be learned by practice of the disclosure.

In accordance with one aspect of the present disclosure, a vehicleincludes: an input unit configured to receive an execution command forspeech recognition; a calculator configured to calculate a time in whichthe vehicle is expected to arrive at an obstacle existing on a road onwhich the vehicle travels; and a speech recognition controllerconfigured to compare the calculated time in which the vehicle isexpected to arrive at the obstacle to a time in which a voice commandinput is expected to be completed to determine whether to performdynamic noise removal pre-processing.

The vehicle may further include a speed sensor configured to detect adriving speed of the vehicle, and to provide information about thedriving speed of the vehicle.

The calculator may calculate the time in which the vehicle is expectedto arrive at the obstacle existing on the road on which the vehicletravels, based on information about the obstacle existing on the road onwhich the vehicle travels, received from a navigation module, andinformation about the driving speed of the vehicle, received from thespeed sensor.

The calculator may calculate the time in which the vehicle is expectedto arrive at the obstacle existing on the road on which the vehicletravels, based on the information about the obstacle existing on theroad on which the vehicle travels, sensed through a vision sensor, andinformation about the driving speed of the vehicle, received from thespeed sensor.

The speech recognition controller may compare the calculated time inwhich the vehicle is expected to arrive at the obstacle to a time inwhich a voice command input is expected to be completed, and activatethe dynamic noise removal pre-processing, if the speech recognitioncontroller determines that the vehicle arrives at the obstacle beforethe voice command input is expected to be completed.

The vehicle may further include an impact sensor configured to determinewhether an impact is generated due to the obstacle existing on the roadon which the vehicle travels.

If the speech recognition controller determines that the vehicle arrivesat the obstacle within the time in which the voice command input isexpected to be completed, the speech recognition controller maydetermine whether an impact is generated due to the obstacle, throughthe impact sensor, and determines whether to activate the dynamic noiseremoval pre-processing based on the result of the determination.

In accordance with another aspect of the present disclosure, a vehicleincludes: an input unit configured to receive an execution command forspeech recognition; a navigation module configured to transferinformation about an obstacle existing on a road on which the vehicletravels to a speech recognition controller; and the speech recognitioncontroller configured to compare a time in which the vehicle is exceptedto arrive at the obstacle based on the information transferred from thenavigation module to a time in which a voice command is input todetermine whether to perform dynamic noise removal pre-processing.

The vehicle may further include a speed sensor configured to detect adriving speed of the vehicle, and to provide information about thedriving speed of the vehicle.

The speech recognition controller may calculate the time in which thevehicle is expected to arrive at the obstacle existing on the road onwhich the vehicle travels, based on information about the obstacleexisting on the road on which the vehicle travels, received from thenavigation module, and information about the driving speed of thevehicle, received from the speed sensor.

The speech recognition controller may calculate the time at which thevehicle is expected to arrive at the obstacle existing on the road onwhich the vehicle travels, based on the information about the obstacleexisting on the road on which the vehicle travels, sensed through avision sensor, and information about the driving speed of the vehicle,received from the speed sensor.

The speech recognition controller may compare the time in which thevehicle is expected to arrive at the obstacle to a time in which a voicecommand input is expected to be completed, and activate the dynamicnoise removal pre-processing, if the speech recognition controllerdetermines that the vehicle arrives at the obstacle before the voicecommand input is expected to be completed.

The vehicle may further include an impact sensor configured to determinewhether an impact is generated due to the obstacle existing on the roadon which the vehicle travels.

If the speech recognition controller determines that the vehicle arrivesat the obstacle within the time in which the voice command input isexpected to be completed, the speech recognition controller maydetermine whether an impact is generated due to the obstacle, throughthe impact sensor, and determine whether to activate the dynamic noiseremoval pre-processing based on the result of the determination.

The vehicle may further include a controller configured to control thenavigation module and the speech recognition controller.

In accordance with still another aspect of the present disclosure, amethod of controlling a vehicle includes: activating speech recognitionupon receiving an execution command to start speech recognition;calculating a time at which the vehicle is expected to arrive at anobstacle existing on a road on which the vehicle travels; and comparingthe calculated time in which the vehicle is expected to arrive at theobstacle to a time in which a voice command input is expected to becompleted to determine whether to perform dynamic noise removalpre-processing.

The calculating of the time at which the vehicle is expected to arriveat the obstacle existing on the road on which the vehicle travels mayinclude calculating the time in which the vehicle is expected to arriveat the obstacle existing on the road on which the vehicle travels, basedon information about the obstacle existing on the road on which thevehicle travels, received from a navigation module, and informationabout a driving speed of the vehicle, received from a speed sensor.

The calculating of the time at which the vehicle is expected to arriveat the obstacle existing on the road on which the vehicle travels mayinclude calculating the time at which the vehicle is expected to arriveat the obstacle existing on the road on which the vehicle travels, basedon information about the obstacle existing on the road on which thevehicle travels, sensed through a vision sensor, and information about adriving speed of the vehicle, received from the speed sensor.

The determining of whether to perform dynamic noise removalpre-processing may include: upon determination that the calculated timeis within the time in which the voice command input is expected to becompleted, activating the dynamic noise removal pre-process; and upondetermination that the calculated time is greater than the time in whichthe voice command input is expected to be completed, performing a staticnoise removal pre-process without activating the dynamic noise removalpre-process.

The determining of whether to perform dynamic noise removalpre-processing may include: upon determination that the vehicle arrivesat the obstacle within the time in which the voice command input isexpected to be completed, determining whether an impact is generated dueto the obstacle, through an impact sensor; upon determination that theimpact is generated due to the obstacle, activating the dynamic noiseremoval pre-processing; and upon determination that the impact is notgenerated due to the obstacle, performing a static noise removalpre-processing without activating the dynamic noise removalpre-processing.

BRIEF DESCRIPTION OF THE DRAWINGS

These and/or other aspects of the disclosure will become apparent andmore readily appreciated from the following description of theembodiments, taken in conjunction with the accompanying drawings ofwhich:

FIG. 1 is a perspective view briefly showing an outer appearance of avehicle according to an embodiment of the present disclosure;

FIG. 2 shows the interior of a vehicle according to an embodiment of thepresent disclosure;

FIGS. 3 and 4 are control block diagrams of vehicles supporting a speechrecognition function, according to embodiments of the presentdisclosure;

FIG. 5 is a flowchart illustrating a method in which a vehicle activatesa dynamic noise removal function according to an expected time ofarrival at an obstacle, according to an embodiment of the presentdisclosure;

FIG. 6 is a view for describing a method of supporting a speechrecognition function through a display screen, according to anembodiment of the present disclosure;

FIGS. 7 and 8 show a vehicle traveling on a road, and an obstaclelocated on a driving path of the vehicle; and

FIGS. 9 and 10 are flowcharts illustrating methods in which a userinterfaces with components in a vehicle to perform noise removalpre-processing, according to embodiments of the present disclosure.

DETAILED DESCRIPTION

Reference will now be made in detail to the embodiments of the presentdisclosure, examples of which are illustrated in the accompanyingdrawings, wherein like reference numerals refer to like elementsthroughout.

Hereinafter, embodiments of the present disclosure will be described indetail with reference to the accompanying drawings.

FIG. 1 is a perspective view briefly showing an outer appearance of avehicle according to an embodiment of the present disclosure, FIG. 2shows the interior of a vehicle according to an embodiment of thepresent disclosure, and FIG. 3 is a control block diagram of a vehiclethat compares information about the direction of a road to informationabout the direction of the vehicle to determine a driving direction,according to an embodiment of the present disclosure.

Referring to FIG. 1, the vehicle 1 may include a body 80 forming anouter appearance of the vehicle 1, and a plurality of wheels 93 and 94to move the vehicle 1. The body 80 may include a hood 81, a plurality offront fenders 82, a plurality of doors 84, a trunk lid 85, and aplurality of quarter panels 86.

The body 80 may include a front window 87 installed in the front part ofthe body 80 to provide a front view of the vehicle 1, a plurality ofside windows 88 to provide side views of the vehicle 1, a plurality ofside-view mirrors 91 and 92 to provide rear and side views of thevehicle 1, and a rear window 90 installed in the rear part of the body80 to provide a rear view of the vehicle 1. Hereinafter, the interior ofthe vehicle 1 will be described in detail.

The vehicle 1 may include an air conditioner. The air conditioner isequipment to control air-conditioned environments includingindoor/outdoor environmental conditions of the vehicle 1, airintake/exhaust, air circulation, and air-conditioned states,automatically or according to a user's control command. For example, thevehicle 1 may include an air conditioner that can perform both heatingand cooling to discharge heated or cooled air through air vents 153 tothus control the inside temperature of the vehicle 1.

Meanwhile, in the interior of the vehicle 1, an Audio/Video/Navigation(AVN) terminal 100 may be provided. The AVN terminal 100 is a terminalcapable of providing audio and video functions, in addition to anavigation function of providing a user with information about a routeto a destination. The AVN terminal 100 may be also called a navigationterminal, or another name used in common by those skilled in the art.

The AVN terminal 100 may selectively display at least one of an audioscreen, a video screen, and a navigation screen through a display unit101, and also display various control screens related to the control ofthe vehicle 1 or screens related to additional functions that can beexecuted on the AVN terminal 100.

According to an embodiment, the AVN terminal 100 may interwork with theair conditioner described above to display various control screensrelated to the control of the air conditioner through the display unit101. Also, the AVN terminal 100 may control the operation state of theair conditioner to adjust an air-conditioned environment inside thevehicle 1. Also, the AVN terminal 100 may display a map on which a routeto a destination is represented through the display unit 101, althoughnot limited to this.

Meanwhile, the display unit 101 may be positioned in a center fascia 11which is the central area of a dashboard 10. According to an embodiment,the display unit 101 may be a Liquid Crystal Display (LCD), a LightEmitting Diode (LED) display, a Plasma Display Panel (PDP) display, anOrganic Light Emitting Diode (OLED) display, or a Cathode Ray Tube (CRT)display, although not limited to these.

In the interior of the vehicle 1, a speaker 143 may be provided tooutput sound. Accordingly, the vehicle 1 may output sound required toperform an audio function, a video function, a navigation function, andother additional functions, through the speaker 143. For example, thevehicle 1 may provide a driver with information about a route to adestination, through the speaker 143, although not limited to this.

A navigation input unit 102 may be located in the center fascia 11 whichis the central area of the dashboard 10. A driver may manipulate thenavigation input unit 102 to input various control commands orinformation about a destination.

Meanwhile, the navigation input unit 102 may be located close to thedisplay unit 101, and implemented as a hard key type. If the displayunit 101 is implemented as a touch screen, the display unit 101 mayperform the function of the navigation input unit 102, in addition to adisplay function.

Meanwhile, a center console 40 may include a center input unit 43 of ajog shuttle type or a hard key type. The center console 40 may bepositioned between a driver seat 21 and a passenger seat 22, and includea gear transmission lever 41 and a tray 42. The center input unit 43 mayperform all or a part of functions of the navigation input unit 102.

Referring to FIG. 3, the vehicle 1 may further include an input unit110, a localization sensor 130, a speed sensor 140, a speech recognitionmodule 150, a navigation module 160, an impact sensor 170, a visionsensor 180, and a speech input unit 188, in addition to theabove-described components.

The speech recognition module 150 and the navigation module 160 may beintegrated into at least one System On Chip (SOC) installed in thevehicle 1, and may be operated by a processor. However, if the vehicle 1includes a plurality of SOCs, the speech recognition module 150 and thenavigation module 160 may be integrated into the plurality of SOCs.

The input unit 110 may be implemented as the navigation input unit 102and the center input unit 43. Also, the input unit 110 may beimplemented as an input unit disposed in a side part of the steeringwheel 12, although not limited to this. If the display unit 101 isimplemented as a touch screen, the display unit 110 may perform thefunctions of the input unit 110.

The input unit 110 may receive various control commands from a driver ora passenger (hereinafter, the driver or the passenger will be referredto as a user). For example, the input unit 110 may receive a command forexecuting a speech recognition function, as well as commands forexecuting the functions of specific equipment in the vehicle 1, such asa music search command, a destination search command, etc.

Also, in the vehicle 1, the speech input unit 188 may be provided. Thespeech input unit 188 may receive a users voice command. For example,the speech input unit 188 may receive a voice command uttered from adriver through a microphone, and convert the voice command into anelectrical signal.

According to an embodiment, the speech input unit 188 may be, as shownin FIG. 2, installed on a headlining 13. However, the speech input unit188 may be installed on the dash board 10, on the steering wheel 12, oron any appropriate location at which a driving users speech can beeffectively received.

Meanwhile, the vehicle 1 may include a communication unit 120. Thecommunication unit 120 may transmit/receive data to/from an externaldevice through a wired/wireless communication network. The wirelesscommunication network enables a device to transmit/receive signalscontaining data to/from another device in a wireless fashion. Forexample, the wireless communication network may include a 3Generation(3G) communication network, a 4Generation (4G) communication network,and a Bluetooth communication network, although not limited to these.

Also, the wired communication network enables a device totransmit/receive signals containing data to/from another device in awired fashion. For example, the wired communication network may includea Peripheral Component Interconnect (PCI), PCI-express, and a UniversalSerial Bus (USB), although not limited to these.

For example, the communication unit 110 may receive various datacorresponding to a users voice command from an external server.According to an embodiment, if a voice command related to today'sweather is received from a user through the input unit 110, thecommunication unit 120 may receive data about today's weather from anexternal server through a wireless communication network.

The localization sensor 130 may acquire location information of thevehicle 1. The location information of the vehicle 1 may be informationindicating the location of the vehicle 1. For example, the locationinformation may include coordinate information, such as longitude,latitude, and altitude, although not limited to these. That is, thelocation information of the vehicle 1 may be any information indicatingthe location of the vehicle 1.

Meanwhile, the localization sensor 130 may be a Global PositioningSystem (GPS) that receives location information of an object from asatellite, or a Differential Global Positioning System (DGPS) that is anenhanced GPS for estimating the location of an object with greataccuracy, although not limited to these.

Location information that is transmitted from a satellite to a GPS onthe ground may have errors. For example, when there are N (N≧2) GPSslocated close to each other, the N GPSs may have similar errors. In thiscase, the DGPS may cancel such errors of the N GPSs to thereby acquiremore accurate data. Accordingly, the vehicle 1 may determine a distanceto an obstacle, based on the location information of the vehicle 1detected through the localization sensor 130 and location information ofthe obstacle stored in map database 161, which will be described indetail later.

The speed sensor 140 may detect a driving speed of the vehicle 1.Herein, the speed sensor 140 may be any one of various kinds of speedsensors including a reed switch type speed sensor, a photoelectric speedsensor, and an electronic speed sensor, although not limited to these.

The impact sensor 170, which may be implemented by an inertial sensor,may sense any impact applied to the vehicle 1. For example, when animpact greater than a predetermined strength is applied to the vehicle1, the impact sensor 170 may output a signal. According to anembodiment, the impact sensor 170 may adjust the magnitude of a signalaccording to an impact strength to thereby provide information aboutimpact quantity.

The vision sensor 180 may identify an object, such as an obstacle oranother vehicle, existing around the vehicle 1 from a peripheral imageof the vehicle 1, and also calculate a distance to the identifiedobject. For example, the vision sensor 180 may identify an objectexisting ahead of the vehicle 1, and calculate a distance between thevehicle 1 and the identified object.

Meanwhile, referring to FIG. 3, the navigation module 160 may includethe map database 161, and a navigation controller 162. The map database161 may store map data. Herein, the map data may include variousinformation, such as roads, buildings, etc., which can represent a map.Also, the map data may include information about Point of Interest(P01).

In addition, the map data may include environmental information aboutroads included in the map. The environmental information about roadsmeans driving environment information of roads. Also, the environmentalinformation about roads may include information about various facilitiesexisting on or around roads, and information indicating areas wheretraffic accidents often took place. For example, the environmentalinformation about roads may be information about obstacles existing onroads, such as information indicating the locations of speed humps, andinformation about unpaved roads.

Herein, the obstacle may be any object existing on a road, which maycollide with a traveling vehicle to generate noise. A calculator 151 maycalculate a time of arrival at an obstacle based on information aboutobstacles stored in the map database 161. This operation will bedescribed in detail, later.

Meanwhile, the map database 161 may be at least one type of storagemedium among a flash memory type, a hard disk type, a multimedia cardmicro type, card type memory (for example, Secure Digital (SD) oreXtreme Digital (XD) memory), Random Access Memory (RAM), Static RandomAccess Memory (SRAM), Read-Only Memory (ROM), Electrically ErasableProgrammable Read-Only Memory (EEPROM), magnetic memory, a magneticdisk, and an optical disk. However, the map database 161 is not limitedto the above-mentioned devices, and may be implemented as any other typeof storage medium well-known to those skilled in the art.

The map database 161 may store map data of all regions or map data ofpredetermined regions. The vehicle 1 may receive necessary map data froman external server through the communication unit 120.

Meanwhile, the navigation controller 162 may control overall operationsof the navigation module 160. For example, the navigation controller 162may decide a route to a destination based on the map data stored in themap database 161, and control operations of various functions that aresupported by the navigation module 160.

Meanwhile, referring to FIG. 3, the speech recognition module 150 mayinclude the calculator 151 and a speech recognition controller 152. Thecalculator 151 and the speech recognition controller 152 may beintegrated into a SOC installed in the vehicle 1, and operated by aprocessor.

The calculator 151 may calculate a time of arrival at an obstacleexisting on a road on which the vehicle 1 travels. In order to calculatea time of arrival at an obstacle, the calculator 151 may calculate adistance to the obstacle from the vehicle 1, based on locationinformation of the vehicle 1 and location information of the obstacle.

The location information of the vehicle 1 may be acquired through thelocalization sensor 130, as described above, and the locationinformation of the obstacle may be acquired from the map database 161installed in the navigation module 160. Accordingly, the calculator 151may calculate a time in which the vehicle 1 is expected to arrive at theobstacle, that is, a time in which the vehicle 1 is expected to collidewith the obstacle, based on the distance between the vehicle 1 and theobstacle and a driving speed of the vehicle 1 detected by the speedsensor 140.

The speech recognition controller 152 may control overall operations ofthe speech recognition module 150. For example, the speech recognitioncontroller 152 may extract a speech waveform from a users voice command,and interwork with the communication unit 120 to transfer the speechwaveform to a speech recognition server. Then, the speech recognitioncontroller 152 may receive the result of speech recognition from thespeech recognition server through the communication unit 120, andgenerate a control signal for controlling a specific device in thevehicle 1 based on the result of speech recognition.

Meanwhile, the speech recognition controller 152 may perform noiseremoval pre-processing in order to extract more accurate data from theusers voice command. Meanwhile, noise may be classified into dynamicnoise and static noise. The static noise is noise that is constantlygenerated when a vehicle travels. For example, the static noise mayinclude noise generated by the sound of wind and noise generated by thedriving of the engine when the vehicle travels. In contrast, the dynamicnoise is noise generated temporarily. For example, the dynamic noise mayinclude noise generated at a specific moment, such as noise generatedwhen a traveling vehicle collides with an obstacle.

Since the static noise is constantly generated, the static noise may beconstantly added to a voice command uttered by the user. However, sincethe dynamic noise is generated at a specific moment, the dynamic noisemay or may not be generated when the user utters a voice command.

Accordingly, if no dynamic noise is generated, the dynamic noise removalpre-processing does not need to be performed. Accordingly, the vehicle 1may predict generation of dynamic noise, and perform dynamic noiseremoval pre-processing only when generation of dynamic noise ispredicted, thereby improving the accuracy of speech recognition whilereducing overload according to a speech recognition process.

Meanwhile, the speech recognition controller 152 may compare a time inwhich a voice command input is expected to be completed to a time inwhich the vehicle 1 is expected to arrive at an obstacle to determinewhether to perform dynamic noise removal pre-processing. For example,due to various obstacles existing on a road, an impact may be applied tothe vehicle 1. If such an impact is applied to the vehicle 1 when theuser inputs a voice command, it is difficult to accurately recognize theusers voice command since dynamic noise is included in the voicecommand. Accordingly, the vehicle 1 may predict generation of dynamicnoise, and activate a dynamic noise removal pre-processing function ifgeneration of dynamic noise is predicted, thereby accurately recognizinga users voice command.

A time in which the voice command input is expected to be completed maybe a time in which a user finishes utterance of a voice command onaverage. However, when a plurality of users utter the same content withtheir voices, they may finish their utterances at different times.Accordingly, the speech recognition controller 152 may set a time inwhich users finish utterances of a voice command on average to a voicecommand input completion time, in advance, and determine whether thevehicle 1 arrives at an obstacle and dynamic noise is generated due tocollision with the obstacle before the voice command input completiontime elapses. The voice command input completion time may be setautomatically by a designer of the speech recognition module 150, ormanually by a user.

Accordingly, if the speech recognition controller 152 determines thatthe vehicle 1 will arrive at an obstacle before the voice command inputcompletion time elapses, the speech recognition controller 152 maydetermine that dynamic noise will be generated, and activate the dynamicnoise removal pre-processing function. As another example, if the speechrecognition controller 152 determines that the vehicle 1 will arrive atan obstacle after the voice command input completion time elapses, thespeech recognition controller 152 may determine that no dynamic noisewill be generated, and may not activate the dynamic noise removalpre-processing function.

However, the speed of the vehicle 1 may change, and a time in which anactual voice command input is completed may also change. Accordingly,the speech recognition controller 152 may determine whether an impact isapplied to the vehicle 1 while an actual voice command is input todetermine whether to perform dynamic noise removal pre-processing,thereby determining in stages whether or not to perform dynamic noiseremoval pre-processing.

That is, the speech recognition controller 152 may determine whetherdynamic noise is included in a voice command to determine activation ofthe dynamic noise removal pre-processing function, and also, determinewhether dynamic noise is generated while an actual voice command isinput to determine whether to activate the dynamic noise removalpre-processing function.

Also, if the speech recognition controller 152 determines that thevehicle 1 will not arrive at any obstacle within the voice command inputcompletion time, the speech recognition controller 152 may perform onlystatic noise removal pre-processing. Also, there is a case that althoughthe speech recognition controller 152 determines that the vehicle 1 willarrive at an obstacle within the voice command input completion time, noimpact is sensed when an actual voice command is received, or thestrength of a sensed impact is smaller than a predetermined strength soas for the speech recognition controller 152 to determine that theimpact has no influence on recognition of the voice command. In thiscase, the speech recognition controller 152 may perform only staticnoise removal pre-processing, thereby preventing overload of a voicecommand recognition process, and quickly processing a voice command.

A controller 185 may be a processor for performing various operationsand control processes, such as a processor installed in the AVN terminal100, or may be one of various processors well-known in the related art.

Also, the controller 185 may control overall operations of the vehicle1. More specifically, the controller 185 may control operations of allcomponents (for example, the display unit 101 and the speaker 143)installed in the vehicle 1, as well as various modules such as thespeech recognition module 150 and the navigation module 160 installed inthe AVN terminal 100. The controller 185 may generate control signalsfor controlling the components of the vehicle 1 to control theoperations of the individual components.

For example, the controller 185 may control the communication unit 120to update the map database 161. According to an embodiment, when mapdata needs to be updated due to a reason such as new road building, thecontroller 185 may access a wireless communication network through thecommunication unit 120 to receive data from an external server, andupdate the map database 161. Thereby, the vehicle 1 can more accuratelydetermine information about locations of obstacles.

Meanwhile, referring to FIG. 4, the AVN terminal 100 may include thespeech recognition module 150, the navigation module 160, and acontroller 190. The speech recognition module 150, the navigation module160, and the controller 190 may be integrated into a SOC installed inthe AVN terminal 100.

The controller 190 may control overall operations of the speechrecognition module 150 and the navigation module 160, while controllingoverall operations of devices in the vehicle 1. That is, the controller190 may include the controller 185, the speech recognition controller152, and the navigation controller 162 shown in FIG. 3, and accordingly,a detailed description for the controller 190 will be omitted.

According to an embodiment, the calculator 151, the speech recognitioncontroller 152, and the navigation controller 162 may be integrated intoa SOC installed in the AVN terminal 100. That is, the controller 190 maybe installed in the AVN terminal 100 to perform overall operations ofthe above-described components.

Hereinafter, operation flow of a vehicle will be briefly described.

FIG. 5 is a flowchart illustrating a flowchart in which a vehicleactivates a dynamic noise removal function according to an expected timeof arrival at an obstacle, according to an embodiment of the presentdisclosure, FIG. 6 is a view for describing a flowchart of supporting aspeech recognition function through a display screen, according to anembodiment of the present disclosure, and FIGS. 7 and 8 show a vehicletraveling on a road, and an obstacle located on a driving path of thevehicle. The following description will be given with reference to FIGS.5 to 8.

Referring to FIG. 5, a vehicle may activate a speech recognitionfunction, in operation 500. The vehicle may receive a command foractivating a speech recognition module through any one of devicescapable of receiving various control commands from a user. Accordingly,the vehicle may activate the speech recognition module to convert into astandby state for receiving a users voice command.

If the speech recognition module is activated, the vehicle may request auser to input a voice command. For example, as shown in FIG. 6, thevehicle may display a pop-up message 300 on a display screen to requesta user to input a voice command. Also, the vehicle may output beep soundthrough a speaker to request a user to input a voice command.

The vehicle may determine whether an obstacle exists on a road on whichthe vehicle travels, in operation 510. The obstacle may be any obstacleexisting on a road. For example, the obstacle may be a speed hump 200 ona road, as shown in FIG. 7. That is, the obstacle may be any obstaclethat may collide with a traveling vehicle to generate noise.

The vehicle may determine existence of an obstacle based on roadenvironment information stored in map database, or sense any obstacleahead through a vision sensor to determine existence of an obstacle.

If the vehicle determines that an obstacle exists, the vehicle maycalculate an expected time of arrival at the obstacle, in operation 520.According to an embodiment, the vehicle may acquire its own locationinformation through a localization sensor, and calculate a distance tothe obstacle, based on the acquired location information and informationabout the obstacle stored in the map database. Also, the vehicle maydetect a driving speed through a speed sensor. Accordingly, the vehiclemay calculate a time of arrival at the obstacle, based on the drivingspeed and the distance to the obstacle.

As another example, the vehicle may calculate a distance to a sensedobstacle through the vision sensor. Referring to FIG. 7, the vehicle maydetect a speed hump 200 existing in a front view, and calculate adistance to the speed hump 200, through the vision sensor. Accordingly,the vehicle may calculate an expected time of arrival at the obstacle,based on a driving speed detected through the speed sensor and thedistance to the obstacle calculated through the vision sensor.

The vehicle may compare the expected time of arrival at the obstacle toa time in which a voice command input is completed on average todetermine whether dynamic noise removal is needed, in operation 530. Forexample, if a voice command input is completed before the vehiclearrives at the obstacle, no dynamic noise due to an impact may begenerated until the voice command input is completed. In this case, thevehicle does not need to remove dynamic noise. However, if the vehiclearrives at the obstacle before a voice command input is completed,dynamic noise may be added to the voice command. In this case, thevehicle may remove dynamic noise added to the received voice command tothereby raise the accuracy of speech recognition. That is, the vehiclemay predict whether or not dynamic noise will be added to a voicecommand to determine whether or not to remove dynamic noise, therebyimproving the accuracy of speech recognition.

Meanwhile, the driving speed of the vehicle and the driving environmentsof roads may change every moment. For example, the road environmentinformation stored in the map database may change due to roadconstruction and the like. Accordingly, no obstacle may exist on a roadon which the vehicle travels.

As another example, if a voice command input is completed earlier than atime in which a voice command input is completed on average, the resultof prediction about whether or not the vehicle will collide with anobstacle while a voice command is input may not reflect a realsituation.

For this reason, the vehicle according to the current embodiment maydetermine whether the vehicle collides with an obstacle, that is,whether the vehicle arrives at an obstacle, within a time in which anactual voice command input is completed, through an impact sensor,thereby preventing other non-dynamic noise from being removed to makerecognition of a voice command difficult.

Accordingly, if no obstacle exists on a road on which the vehicletravels, or if the vehicle collides with an obstacle after an actualvoice command input is completed, contrary to expectations, the vehiclemay perform only static noise removal pre-processing, in operation 540.Also, if the vehicle collides with an obstacle before an actual voicecommand input is completed, the vehicle may perform dynamic noiseremoval pre-processing, thereby improving the accuracy of speechrecognition, in operation 550.

FIGS. 9 and 10 are flowcharts illustrating methods in which a userinterfaces with components in a vehicle to perform noise removalpre-processing, according to embodiments of the present disclosure. Thefollowing description will be given with reference to FIGS. 9 and 10.

Hereinafter, the operation of the speech recognition module 150 and theoperation of the navigation module 160 (see FIG. 4) will be separatelydescribed. However, the operations of the speech recognition module 150and the navigation module 160 may be performed by the controller 190(see FIG. 4) installed in the AVN terminal, as described above.

Referring to FIG. 9, a user U may input a speech recognition startcommand using one of various components in a vehicle, in operation 900.For example, the user U may input a speech recognition start commandthrough a navigation input unit or an input unit provided on one side ofa steering wheel, during driving.

The speech recognition module 150 may receive the speech recognitionstart command, and request the navigation module 160 to send informationabout obstacles, in operation 905. The information about obstacles mayinclude information about kinds and locations of obstacles. Meanwhile,the speech recognition module 150 may receive information about acurrent location of the vehicle, detected through a localization sensor.

Accordingly, the speech recognition module 150 may receive theinformation about obstacles, in operation 910, to calculate a distanceto an obstacle ahead of the vehicle based on the information about thelocations of obstacles and the information about the current location ofthe vehicle. Also, the speech recognition module 150 may receiveinformation about a driving speed detected through the speed sensor 140,in operation 915.

Then, the speech recognition module 150 may calculate a time of arrivalat the obstacle, based on the distance to the obstacle and the drivingspeed, in operation 920. Also, the speech recognition module 150 maycompare the time of arrival at the obstacle to a time in which a voicecommand input is completed, and thus determine whether the vehiclecollides with the obstacle when the user inputs a voice command. Thespeech recognition module 150 may determine whether to activate adynamic noise removal pre-processing function, based on the result ofthe determination.

According to an embodiment, the speech recognition module 150 maydetermine whether the vehicle collides with the obstacle when the userinputs the voice command, using Equation (1) below.

T<D/V<T+S  (1)

Herein, T represents an average time taken for a user to start uttering,and S represents an average time for which a user inputs a voicecommand. Also, V represents a driving speed of the vehicle, and Drepresents a distance to an obstacle from the fore end of the vehicle.

For example, noise removal may be required when a voice command receivedfrom a user includes noise. Accordingly, when a user inputs no voicecommand, noise does not have influence on recognizing a user's voicecommands. Accordingly, the speech recognition module 150 may determinewhether noise is generated due to collision with an obstacle for anaverage time in which a user inputs a voice command, to thus determinewhether to perform noise removal pre-processing.

Meanwhile, the speech recognition module 150 may output beep soundthrough a speaker to request the user U to input a voice command, inoperation 925. Then, the vehicle may receive a voice command utteredfrom the user U, through a speech input unit, in operation 930.Meanwhile, the speech recognition module 150 may determine whether thevehicle arrives at an obstacle within a time in which the voice commandinput is expected to be completed, in operation 935.

If the speech recognition module 150 determines that the vehicle willarrive at the obstacle within the time in which the voice command inputis expected to be completed, the speech recognition module 150 maydetermine whether an impact is generated while an actual voice commandis input. At this time, the speech recognition module 150 may receiveinformation about impact generation from the impact sensor 170, inoperation 940, to determine whether an impact is generated, in operation945.

Accordingly, if no impact is generated within a time in which an actualvoice command input is completed although the vehicle is expected toarrive at the obstacle within the expected time, the speech recognitionmodule 150 may perform only static noise removal pre-processing, inoperation 950. In contrast, if the vehicle is expected to arrive at theobstacle within the expected time, and an impact is generated within atime in which an actual voice command input is completed, the speechrecognition module 150 may perform dynamic noise removal pre-processing,in operation 955. For example, the speech recognition module 150 maydetermine whether dynamic noise is generated while an actual voicecommand is input, based on Equation (2) below.

B<G<E  (2)

Herein, B represents a time at which it is determined that a voicecommand input starts. For example, the speech recognition module 150 maydetermine a time at which beep sound is output as a time at which avoice command input starts. The user U may utter voice when apredetermined time elapses after beep sound is output. Accordingly, thespeech recognition module 150 may determine that a voice command inputstarts when a predetermined time elapses after beep sound is output.

E represents a time at which it is determined that a sound command inputis completed. For example, the speech recognition module 150 maydetermine that a voice command input is completed when a voice waveformwhich is a major portion of an input voice waveform is no longer input.Or, the speech recognition module 150 may determine that a voice commandinput is completed when a predetermined voice command input time haselapsed.

G represents a time at which an impact that is greater than or equal toa predetermined strength is sensed through an impact sensor. That is,the speech recognition module 150 may determine whether to activate thedynamic noise removal pre-processing function depending on whether animpact is generated within a time in which an actual voice command isinput.

Meanwhile, operations of FIG. 10 are the same as those of FIG. 9, exceptthat the speech recognition module 150 receives information about anobstacle from the vision sensor 180 (see FIGS. 3 and 4), instead of thenavigation module 160. Therefore, a description of operations 1000through 1055 in FIG. 10 is omitted to avoid redundancy. As describedabove, the vision sensor 180 may be installed in the vehicle to senseany obstacle from a front view of the vehicle, as shown in FIG. 8.Accordingly, the speech recognition module 150 may receive informationabout a distance to an obstacle from the vision sensor 180.

The method according to the above-described embodiment can be embodiedin the form of program instructions, which can be performed throughvarious computer means, and can be written in computer-readablerecording medium. The computer-readable recording medium can includeprogram instructions, data files, data structures, and the combinationthereof. The program instructions stored in the storage medium can bedesigned and configured specifically for an exemplary embodiment or canbe publically known and available to those who are skilled in the fieldof computer software. Examples of the computer-readable recording mediumcan include magnetic media, such as a hard disk, a floppy disk, and amagnetic tape, optical media, such as CD-ROM and DVD, magneto-opticalmedia, such as a floptical disk, and hardware devices, such as ROM, RAMand flash memory, which are specifically configured to store and runprogram instructions.

Examples of program instructions include both machine code, such asproduced by a compiler, and high-level language code that may beexecuted on the computer using an interpreter. The hardware devices maybe configured to act as one or more software modules in order to performthe operations of the above-described embodiments, or vice versa.

Although embodiments have been described by specific examples anddrawings, it will be understood to those of ordinary skill in the artthat various adjustments and modifications are possible from the abovedescription. For example, although the described techniques areperformed in a different order, and/or the described system,architecture, device, or circuit component are coupled or combined in adifferent form or substituted/replaced with another component orequivalent, suitable results can be achieved.

Therefore, other implementations, other embodiments, and thingsequivalent to claims are within the scope of the claims to be describedbelow.

What is claimed is:
 1. A vehicle comprising: an input unit configured toreceive an execution command for speech recognition; a calculatorconfigured to calculate a time in which the vehicle is expected toarrive at an obstacle existing on a road on which the vehicle travels;and a speech recognition controller configured to compare the calculatedtime in which the vehicle is expected to arrive at the obstacle to atime in which a voice command input is expected to be completed todetermine whether to perform dynamic noise removal pre-processing. 2.The vehicle according to claim 1, further comprising a speed sensorconfigured to detect a driving speed of the vehicle, and to provideinformation about the driving speed of the vehicle.
 3. The vehicleaccording to claim 2, wherein the calculator calculates the time inwhich the vehicle is expected to arrive at the obstacle existing on theroad on which the vehicle travels, based on information about theobstacle existing on the road on which the vehicle travels, receivedfrom a navigation module, and information about the driving speed of thevehicle, received from the speed sensor.
 4. The vehicle according toclaim 2, wherein the calculator calculates the time in which the vehicleis expected to arrive at the obstacle existing on the road on which thevehicle travels, based on the information about the obstacle existing onthe road on which the vehicle travels, sensed through a vision sensor,and information about the driving speed of the vehicle, received fromthe speed sensor.
 5. The vehicle according to claim 1, wherein thespeech recognition controller compares the calculated time in which thevehicle is expected to arrive at the obstacle to the time in which thevoice command input is expected to be completed, and activates thedynamic noise removal pre-processing, if the speech recognitioncontroller determines that the vehicle arrives at the obstacle beforethe voice command input is expected to be completed elapses.
 6. Thevehicle according to claim 1, further comprising an impact sensorconfigured to determine whether an impact is generated due to theobstacle existing on the road on which the vehicle travels.
 7. Thevehicle according to claim 6, wherein if the speech recognitioncontroller determines that the vehicle arrives at the obstacle withinthe time in which the voice command input is expected to be completed,the speech recognition controller determines whether an impact isgenerated due to the obstacle, through the impact sensor, and determineswhether to activate the dynamic noise removal pre-processing based onthe result of the determination.
 8. A vehicle comprising: an input unitconfigured to receive an execution command for speech recognition; anavigation module configured to transfer information about an obstacleexisting on a road on which the vehicle travels to a speech recognitioncontroller; and the speech recognition controller configured to comparea time in which the vehicle is expected to arrive at the obstacle basedon the information transferred from the navigation module to a time inwhich a voice command is input to determine whether to perform dynamicnoise removal pre-processing.
 9. The vehicle according to claim 8,further comprising a speed sensor configured to detect a driving speedof the vehicle, and to provide information about the driving speed ofthe vehicle.
 10. The vehicle according to claim 9, wherein the speechrecognition controller calculates the time in which the vehicle isexpected to arrive at the obstacle existing on the road on which thevehicle travels, based on information about the obstacle existing on theroad on which the vehicle travels, received from the navigation module,and information about the driving speed of the vehicle, received fromthe speed sensor.
 11. The vehicle according to claim 9, wherein thespeech recognition controller calculates the time at which the vehicleis expected to arrive at the obstacle existing on the road on which thevehicle travels, based on the information about the obstacle existing onthe road on which the vehicle travels, sensed through a vision sensor,and information about the driving speed of the vehicle, received fromthe speed sensor.
 12. The vehicle according to claim 8, wherein thespeech recognition controller compares the time in which the vehicle isexpected to arrive at the obstacle to the time in which the voicecommand input is expected to be completed, and activates the dynamicnoise removal pre-processing, if the speech recognition controllerdetermines that the vehicle arrives at the obstacle before the voicecommand input is expected to be completed.
 13. The vehicle according toclaim 8, further comprising an impact sensor configured to determinewhether an impact is generated due to the obstacle existing on the roadon which the vehicle travels.
 14. The vehicle according to claim 13,wherein if the speech recognition controller determines that the vehiclearrives at the obstacle within the time in which the voice command inputis expected to be completed, the speech recognition controllerdetermines whether an impact is generated due to the obstacle, throughthe impact sensor, and determines whether to activate the dynamic noiseremoval pre-processing based on the result of the determination.
 15. Thevehicle according to claim 8, further comprising a controller configuredto control the navigation module and the speech recognition controller.16. A method of controlling a vehicle, comprising: activating speechrecognition upon receiving an execution command to start speechrecognition; calculating a time in which the vehicle is expected toarrive at an obstacle existing on a road on which the vehicle travels;and comparing the calculated time in which the vehicle is expected toarrive at the obstacle to a time in which a voice command input isexpected to be completed to determine whether to perform dynamic noiseremoval pre-processing.
 17. The method according to claim 16, whereinthe calculating of the time in which the vehicle is expected to arriveat the obstacle existing on the road on which the vehicle travelscomprises calculating the time in which the vehicle is expected toarrive at the obstacle existing on the road on which the vehicletravels, based on information about the obstacle existing on the road onwhich the vehicle travels, received from a navigation module, andinformation about a driving speed of the vehicle, received from a speedsensor.
 18. The method according to claim 16, wherein the calculating ofthe time in which the vehicle is expected to arrive at the obstacleexisting on the road on which the vehicle travels comprises calculatingthe time in which the vehicle is expected to arrive at the obstacleexisting on the road on which the vehicle travels, based on informationabout the obstacle existing on the road on which the vehicle travels,sensed through a vision sensor, and information about a driving speed ofthe vehicle, received from the speed sensor.
 19. The method according toclaim 16, wherein the determining of whether to perform dynamic noiseremoval pre-processing comprises: upon determination that the calculatedtime in which the vehicle is expected to arrive at the obstacle iswithin the time in which the voice command input is expected to becompleted, activating the dynamic noise removal pre-process; and upondetermination that the calculated time in which the vehicle is expectedto arrive at the obstacle is greater than the time in which the voicecommand input is expected to be completed, performing a static noiseremoval pre-process without activating the dynamic noise removalpre-process.
 20. The method according to claim 16, wherein thedetermining of whether to perform dynamic noise removal pre-processingcomprises: upon determination that the vehicle arrives at the obstaclewithin the time in which the voice command input is expected to becompleted, determining whether an impact is generated due to theobstacle, through an impact sensor; upon determination that the impactis generated due to the obstacle, activating the dynamic noise removalpre-processing; and upon determination that the impact is not generateddue to the obstacle, performing a static noise removal pre-processingwithout activating the dynamic noise removal pre-processing.